Mastering the Feedback Workflow: Real-Time Course Correction

One of Kai’s most powerful features is the Feedback Workflow – a system that helps you gather student insights during lectures and use that information to adjust your teaching in real-time. This is our recommended starting point for instructors new to Kai.

Why Feedback Workflow Matters

Traditional end-of-semester evaluations tell you what went wrong after it’s too late to fix it. The Feedback Workflow changes this by creating a continuous feedback loop that helps you:

• Identify confusion immediately – Know when students are lost, not weeks later
• Adjust pacing on the fly – Slow down or speed up based on real understanding
• Validate your teaching approach – See what’s working and what needs tweaking
• Boost engagement – Students feel heard when their feedback leads to visible changes

How It Works

Set Strategic Checkpoints

We recommend requesting feedback every 20-30 minutes during lecture. This keeps students engaged without overwhelming them.

Example timing for a 90-minute lecture:

• Minute 25: After introducing new concept
• Minute 50: After working through first example
• Minute 75: After practice problems

Ask the Right Questions

Kai can send different types of feedback requests:

Quick Check-Ins (1-2 questions):

• “How confident do you feel about this concept? (1-5)"
• "What’s the muddiest point so far?”

Deeper Dives (3-4 questions):

• Conceptual understanding
• Pace assessment
• Application readiness
• Specific pain points

Review Instant Insights

As responses come in, Kai aggregates and analyzes them in real-time. You’ll see:

• Confidence levels across the class
• Common confusion points highlighted
• Pacing feedback (too fast vs. too slow)
• Specific questions that need addressing

Adjust Your Course

This is where the magic happens. Based on student feedback, you can:

• Re-explain concepts showing low confidence scores
• Slow down if 60%+ say you’re moving too fast
• Add examples when students request clarification
• Skip review if the class shows high mastery

Real-World Example: Physics 101

Dr. Martinez uses the Feedback Workflow in her 250-student Physics 101 lecture:

Before Feedback Workflow:

• Students sat silently, Dr. Martinez assumed understanding
• Exam revealed 40% didn’t grasp fundamental concepts
• No way to identify struggling students early

After Implementing Feedback Workflow:

• Requests feedback every 25 minutes
• Discovered students were confused about vector notation (week 2!)
• Added 10-minute review session based on feedback
• Result: 73% average response rate, +8% on exam scores

Dr. Martinez’s insight: “Kai let me feel like I was teaching a class of 30, not 250. I finally know what my students are actually thinking.”

Best Practices from Our Team

Start Small

Begin with just 2-3 feedback checkpoints per lecture. Add more as you get comfortable with the rhythm.

Make It Anonymous

Students give more honest feedback when they know it’s anonymous. Kai handles this automatically.

Close the Loop

Always acknowledge feedback you receive:

• “I see many of you are confused about X. Let’s review…"
• "Based on your feedback, we’re going to slow down here…”

This shows students their input matters and increases future participation.

Track Trends Over Time

Don’t just look at individual sessions. Kai’s analytics show patterns:

• Topics that consistently confuse students
• Times of day when engagement drops
• Week-by-week comprehension trends

Common Mistakes to Avoid

❌ Requesting feedback too frequently → Feedback fatigue ✅ Strategic 20-30 minute intervals → Maintains engagement

❌ Ignoring the results → Students stop responding ✅ Visibly acting on feedback → Builds trust and participation

❌ Using only numeric ratings → Loses nuance ✅ Mix quantitative + qualitative → Get the full picture

Getting Started

Week 1: Simple Implementation

Start with this basic 3-question checkpoint:

1. “How confident are you with today’s material? (1-5)"
2. "Are we moving too fast, too slow, or just right?"
3. "What’s the most confusing part so far?”

Week 2-3: Refine Based on Data

Look at your response rates and adjust:

• Low participation? Make questions more specific
• High confidence but poor exam scores? Questions aren’t probing deep enough
• Students rushing through? Reduce number of questions

Week 4+: Optimize Your Rhythm

By now you’ll know what works for your class:

• Ideal timing for your teaching style
• Questions that generate useful insights
• How to act on feedback efficiently

The 80/20 Rule

Here’s our recommendation: 80% of Kai’s value comes from the Feedback Workflow alone. Master this first, then explore other features like Pop Quizzes and SafeStream.

Why? Because feedback:

• Improves every other aspect of your teaching
• Helps you understand what your students actually need
• Creates a foundation for data-driven pedagogy

Technical Setup

Setting up the Feedback Workflow takes less than 10 minutes:

1. Connect Kai to your LMS (Canvas, Moodle, etc.)
2. Set your feedback schedule (timing + questions)
3. Launch during lecture (Kai sends requests automatically)
4. Review dashboard (see results in real-time)

View our quickstart guide for detailed setup instructions.

Measuring Impact

Track these metrics to see your improvement:

• Response rate (target: 70%+)
• Confidence trends (should increase week-over-week)
• Confusion points (should decrease as you adjust)
• Exam correlation (feedback confidence vs. actual performance)

Next Steps

Ready to implement the Feedback Workflow?

1. Read the technical docs: Feedback Workflow Guide
2. See it in action: Watch our demo video
3. Get started: Join the beta

Have questions about the Feedback Workflow? Contact our team – we’re here to help you succeed.